Information processing device, information processing method, and information processing program

ABSTRACT

An advertisement is delivered based on a first limiting element, a specified number of selections, and an expected selection rate. Based on an expected number of selections and an actual number of selections of the advertisement before the end of a counting period, the number of selections to be further needed at the end of the counting period is estimated. For each of a plurality of second limiting elements different from the first limiting element, an actual selection rate of the advertisement by a group, among the recipients of the advertisement, limited by the second limiting element is obtained. Based on the actual selection rates, a limiting element to be added to delivery requirements from among the plurality of second limiting elements is determined. Based on the determined limiting element, the corresponding actual selection rate, and the estimated number of selections, additional recipients of the advertisement are determined.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a National Stage of International Application No.PCT/JP2014/067164, filed Jun. 27, 2014, the contents of which areincorporated herein by reference in its entirety.

TECHNICAL FIELD

The present invention relates to a technique for deliveringadvertisements.

BACKGROUND ART

A technique by which an advertisement deliverer, which receives arequest from an advertiser, makes deliveries of an advertisement, forexample, using emails is conventionally known. In such an advertisement,for example, a link to a web page of an advertiser is embedded. When auser selects the link, the user's terminal device accesses the web page(e.g., Patent Literature 1).

CITATION LIST Patent Literature

Patent Literature 1: JP 2008-257422 A

SUMMARY OF INVENTION Technical Problem

There may be a case where an advertisement deliverer wishes to makedeliveries of an advertisement so that the number of selections of theadvertisement (the number of link clicks) by recipient users during aset period will be greater than or equal to the number of selectionsdesired by an advertiser. In this case, a small number of deliveries ofthe advertisement may cause the problem that the number of actualselections falls short of the advertiser's desired number of selections.On the other hand, an excessively large number of deliveries increasethe probability that the number of actual selections will be greaterthan or equal to the desired number of selections. However, the load ofa server device that delivers the advertisement is increased, andefficiency in deliveries of the advertisement relative to the desirednumber of selections is reduced.

In view of the above point, it is an object of the present invention toprovide an information processing device, an information processingmethod, and an information processing program that allow for moreefficient deliveries of an advertisement while increasing theprobability that the number of selections of the advertisement will begreater than or equal to a specified number of selections.

Solution to Problem

To solve the above problem, the invention according to claim 1 includesestimating means, obtaining means, element determination means,recipient determination means, and delivery control means. Anadvertisement is delivered to recipients who are determined based on afirst limiting element for limiting the recipients, on a specifiednumber of selections until the end of a counting period for counting thenumber of selections of the advertisement, and on an expected selectionrate of the advertisement. The first limiting element and the specifiednumber of selections are included in delivery requirements of theadvertisement. The estimating means estimates the number of selections,of the advertisement, to be further needed at the end of the countingperiod, based on an expected number of selections and an actual numberof selections of the advertisement until a time before the end of thecounting period. For each of a plurality of second limiting elementsthat are different from the first limiting element, the obtaining meansobtains an actual selection rate of the advertisement by a group, amongthe recipients of the advertisement, limited by the second limitingelement. Based on the actual selection rates obtained by the obtainingmeans, the element determination means determines a limiting element tobe added to the delivery requirements from among the plurality of secondlimiting elements. Based on the limiting element determined by theelement determination means, on the actual selection rate obtained forthis limiting element by the obtaining means, and on the number ofselections estimated by the estimating means, the recipientdetermination means determines additional recipients of theadvertisement. The delivery control means controls deliveries of theadvertisement to the additional recipients determined by the recipientdetermination means.

According to this invention, the information processing devicedetermines a limiting element to be added to the delivery requirements,based on an actual selection rate of the advertisement by a grouplimited to by each second limiting element. Based on the determinedlimiting element, the actual selection rate of the limiting element, andthe estimated number of selections, the information processing devicealso determines additional recipients. The actual selection rate of thelimiting element to be added relates to the number of selections throughadditional deliveries that is expected. Thus, the information processingdevice can increase the probability that the number of selections to beadded will be greater than or equal to the number of selections to befurther needed. Consequently, this allows for more efficient deliveriesof an advertisement while increasing the probability that the number ofselections of the advertisement will be greater than or equal to aspecified number of selections.

The invention according to claim 2 is the information processing deviceaccording to claim 1 further including number determination means. Thenumber determination means determines the number of limiting elements tobe added to the delivery requirements, depending on the number ofselections estimated by the estimating means. The element determinationmeans determines the same number of limiting elements as the numberdetermined by the number determination means to be limiting elements tobe added to the delivery requirements.

According to this invention, the information processing device adds adifferent number of limiting elements depending on the number ofselections that are estimated to be further needed, thus efficientlylimiting additional recipients.

The invention according to claim 3 is the information processing deviceaccording to claim 1 or 2 further including adjusting means. Theadjusting means adjusts the number of additional deliveries of theadvertisement, depending on the remaining time until the end of thecounting period. The recipient determination means determines the samenumber of additional recipients as the number of additional deliveriesadjusted by the adjusting means.

According to this invention, the information processing device adjuststhe number of additional deliveries depending on the remaining time,thus further increasing the probability that the number of selections tobe added will be greater than or equal to the number of selections to befurther needed.

The invention according to claim 4 is the information processing deviceaccording to any one of claims 1 to 3 in which when deliveries of asecond advertisement have been made separately around the same time asthose of the advertisement, the estimating means corrects the number ofselections to be further needed at the end of the counting period,depending on the deliveries of the second advertisement.

According to this invention, depending on the deliveries of anotheradvertisement that were made around the same time as those of theadvertisement to be additionally delivered, the information processingdevice corrects the number of selections to be further needed, thusproperly estimating the number of selections to be further needed.

The invention according to claim 5 is the information processing deviceaccording to claim 4 in which when an attribute of an object advertisedby the second advertisement is the same as that of an object advertisedby the advertisement, the estimating means corrects the number ofselections to be further needed at the end of the counting period.

According to this invention, only when an attribute of an objectadvertised by the other advertisement is the same as that of an objectadvertised by the advertisement to be additionally delivered, theinformation processing device can correct the number of selections to befurther needed, thus more properly estimating the number of selectionsto be further needed.

The invention according to claim 6 is an information processing methodperformed by a computer. The method includes the following steps. Anadvertisement is delivered to recipients who are determined based on afirst limiting element for limiting the recipients, on a specifiednumber of selections until the end of a counting period for counting thenumber of selections of the advertisement, and on an expected selectionrate of the advertisement. The first limiting element and the specifiednumber of selections are included in delivery requirements of theadvertisement. The number of selections, of the advertisement, to befurther needed at the end of the counting period is estimated, based onan expected number of selections and an actual number of selections ofthe advertisement until a time before the end of the counting period.For each of a plurality of second limiting elements that are differentfrom the first limiting element, an actual selection rate of theadvertisement by a group, among the recipients of the advertisement,limited by the second limiting element is obtained. Based on theobtained actual selection rates, a limiting element to be added to thedelivery requirements is determined from among the plurality of secondlimiting elements. Based on the determined limiting element, on theactual selection rate obtained for this limiting element, and on theestimated number of selections, additional recipients of theadvertisement are determined. Deliveries of the advertisement to thedetermined additional recipients are controlled.

The invention according to claim 7 causes a computer to function asestimating means, obtaining means, element determination means,recipient determination means, and delivery control means. Anadvertisement is delivered to recipients who are determined based on afirst limiting element for limiting the recipients, on a specifiednumber of selections until the end of a counting period for counting thenumber of selections of the advertisement, and on an expected selectionrate of the advertisement. The first limiting element and the specifiednumber of selections are included in delivery requirements of theadvertisement. The estimating means estimates the number of selections,of the advertisement, to be further needed at the end of the countingperiod, based on an expected number of selections and an actual numberof selections of the advertisement until a time before the end of thecounting period. For each of a plurality of second limiting elementsthat are different from the first limiting element, the obtaining meansobtains an actual selection rate of the advertisement by a group, amongthe recipients of the advertisement, limited by the second limitingelement. Based on the actual selection rates obtained by the obtainingmeans, the element determination means determines a limiting element tobe added to the delivery requirements from among the plurality of secondlimiting elements. Based on the limiting element determined by theelement determination means, on the actual selection rate obtained forthis limiting element by the obtaining means, and on the number ofselections estimated by the estimating means, the recipientdetermination means determines additional recipients of theadvertisement. The delivery control means controls deliveries of theadvertisement to the additional recipients determined by the recipientdetermination means.

Advantageous Effects of Invention

According to the present invention, the information processing devicedetermines a limiting element to be added to the delivery requirements,based on an actual selection rate of the advertisement by a grouplimited to by each second limiting element. Based on the determinedlimiting element, the actual selection rate of the limiting element, andthe estimated number of selections, the information processing devicealso determines additional recipients. The actual selection rate of thelimiting element to be added relates to the number of selections throughadditional deliveries that is expected. Thus, the information processingdevice can increase the probability that the number of selections to beadded will be greater than or equal to the number of selections to befurther needed. Consequently, this allows for more efficient deliveriesof an advertisement while increasing the probability that the number ofselections of the advertisement will be greater than or equal to aspecified number of selections.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a diagram schematically showing an example configuration of aninformation processing system S according to an embodiment.

FIG. 2A is a block diagram schematically showing an exampleconfiguration of an advertisement delivery server 1 according to anembodiment.

FIG. 2B is a diagram showing example functional blocks of a systemcontroller 14 of an advertisement delivery server 1 according to anembodiment.

FIG. 3A is a diagram showing example contents stored in a memberinformation DB 21.

FIG. 3B is a diagram showing example contents stored in a viewinghistory DB 22.

FIG. 3C is a diagram showing example contents stored in a purchasehistory DB 23.

FIG. 3D is a diagram showing example contents stored in an advertisementDB 121.

FIG. 3E is a diagram showing example contents included in deliveryrequirements.

FIG. 3F is a diagram showing example contents stored in an advertisementdelivery history DB 122.

FIG. 3G is a diagram showing example contents stored in a click historyDB 123.

FIG. 4A is a diagram showing example delivery requirements.

FIG. 4B shows an example of an expected CTR and the number of firstdeliveries.

FIG. 4C is a diagram showing an example of how to calculate an estimatednumber of further needed clicks.

FIG. 4D shows an example of information about users who have viewed aweb page for an item that has the same attribute as an item to beadvertised and users who have not viewed the web page, among users whosatisfy recipient requirements.

FIG. 4E shows an example of information about users who have purchasedan item that has the same attribute as the item to be advertised andusers who have not purchased the item, among the users who satisfy therecipient requirements.

FIG. 5A is a diagram showing example actual CTRs of limiting elementsthat are candidates for additional requirements.

FIG. 5B is a diagram showing examples of expected numbers of additionalclicks corresponding to additional requirements.

FIG. 6A shows a process overview from the first deliveries of anadvertisement to the end of a specified period.

FIG. 6B is a flowchart showing an example of a first delivery process inthe system controller 14 of the advertisement delivery server 1according to an embodiment.

FIG. 7A is a flowchart showing an example of an additional deliverycontrol process in the system controller 14 of the advertisementdelivery server 1 according to an embodiment.

FIG. 7B is a flowchart showing an example of afurther-needed-click-count estimation process in the system controller14 of the advertisement delivery server 1 according to an embodiment.

FIG. 8 is a flowchart showing an example of an additionalrequirement/recipient determination process in the system controller 14of the advertisement delivery server 1 according to an embodiment.

FIG. 9 is a flowchart showing an example of a recursive determinationprocess in the system controller 14 of the advertisement delivery server1 according to an embodiment.

FIG. 10 is a flowchart showing an example of the additional deliverycontrol process in the system controller 14 of the advertisementdelivery server 1 according to an embodiment.

FIG. 11 is a flowchart showing an example of thefurther-needed-click-count estimation process in the system controller14 of the advertisement delivery server 1 according to an embodiment.

DESCRIPTION OF EMBODIMENTS

The following describes embodiments of the present invention in detailwith reference to the drawings. The embodiments described below areembodiments in which the present invention is applied to an informationprocessing system.

1. First Embodiment

1-1. Configuration and Functional Overview of Information ProcessingSystem

First, a configuration and a functional overview of an informationprocessing system S according to this embodiment are described withreference to FIG. 1. FIG. 1 is a diagram schematically showing anexample configuration of the information processing system S accordingto this embodiment.

As shown in FIG. 1, the information processing system S includes anadvertisement delivery server 1, an online marketplace server 2, aplurality of store terminals 3, and a plurality of user terminals 4. Theadvertisement delivery server 1 is capable of exchanging data with eachstore terminal 3 and each user terminal 4 over a network NW usingcommunication protocols, such as TCP/IP. The network NW includes, forexample, the Internet, a dedicated communication line (e.g., communityantenna television (CATV) line), a mobile communication network(including base stations), and a gateway.

The advertisement delivery server 1 is a server device that deliversadvertisements, for example, to users who have signed up for apredetermined online marketplace. The advertisement delivery server 1 isan example of an information processing device according to the presentinvention. For example, a predetermined deliverer receives a requestfrom an advertiser and registers details of an advertisement,requirements for delivering the advertisement, and other information onthe advertisement delivery server 1. The advertisement delivery server 1determines users to be recipients of the advertisement, based on theregistered information, and makes deliveries of the advertisement, forexample, as emails. For example, a store in the online marketplace maybe the advertiser. Alternatively, for example, a company or a personthat does not have any store in the online marketplace may be theadvertiser. In the delivered advertisement, for example, a link to a webpage of the advertiser is embedded. The web page identified by the linkmay be, for example, a web page in the online marketplace.Alternatively, the web page identified by the link may be, for example,a web page that displays information about the advertiser or a web pagethat displays information about an item sold by the advertiser. Theadvertisement delivery server 1 includes, for example, an advertisementDB 121, an advertisement delivery history DB 122, a click history DB123, and other databases. The advertisement DB 121 stores, for example,details of advertisements and delivery requirements of theadvertisements. The advertisement delivery history DB 122 storesadvertisement delivery histories. The click history DB 123 stores users'histories of selecting a link in each advertisement.

The online marketplace server 2 is a server device that performs variousprocesses for the online marketplace. In the online marketplace, aplurality of stores sell items. Users who use the online marketplace canpurchase any desired item from any desired store in the onlinemarketplace. For example, the advertisement delivery server 1 sends webpages of the online marketplace and performs processes for item searchesand orders, in response to requests from the user terminals 4. Theonline marketplace server 2 includes, for example, a member informationDB 21, a viewing history DB 22, a purchase history DB 23, and otherdatabases. The member information DB 21 stores information about userswho have signed up for the online marketplace. The viewing history DB 22stores web page viewing histories of the users in the onlinemarketplace. The purchase history DB 23 stores item purchase historiesof the users in the online marketplace. The advertisement deliveryserver 1 is capable of accessing the member information DB 21, theviewing history DB 22, and the purchase history DB 23 through the onlinemarketplace server 2.

The store terminal 3 is a terminal device used by, for example, anemployee of a store in the online marketplace. Using the store terminal3, for example, information about items for sale is entered into theonline marketplace and item order details are checked. For example, thestore may request a deliverer to make deliveries of an advertisement, byemail, fax, or regular mail, or may operate the store terminal 3 so thatthe advertisement delivery server 1 receives a request for deliveries ofan advertisement from the store terminal 3.

The user terminal 4 is a terminal device of a user who purchases itemsfrom the online marketplace. The user terminal 4 accesses the onlinemarketplace server 2 in accordance with an operation by the user toreceive a web page from the online marketplace server 2 and displays theweb page. The user terminal 4 has software, such as a browser and anemail client, installed on it. For example, a personal computer, apersonal digital assistant (PDA), a portable information terminal suchas a smartphone, or a mobile phone is used as the user terminal 4.

An advertiser specifies delivery requirements when requesting deliveriesof an advertisement. The delivery requirements are requirements for adeliverer to follow in making deliveries of the advertisement. Examplesof the delivery requirements include a desired number of clicks, aperiod, and recipient requirements. The number of clicks is the numberof users who clicked a link in a delivered advertisement. Selection of alink in an advertisement is simply referred to as selection of theadvertisement. The advertisement delivery server 1 makes simultaneousdeliveries of an advertisement, for example, at the beginning of theperiod specified by the advertiser. The advertisement delivery server 1counts the number of clicks made from the beginning to the end of thespecified period. The specified period is an example of a countingperiod of the present invention. The desired number of clicks indicateshow many clicks the advertiser desires to be made during the periodspecified by the advertiser. The recipient requirements are requirementsabout users that the advertiser specifies as recipients of theadvertisement. The recipient requirements limit recipients of theadvertisement from among the users of the online marketplace. Examplesof an element item that can be specified in the recipient requirementsinclude gender, age groups, areas of residence, member ranks, a web pageviewing history, an item purchase history, and a delivered advertisementreception history. An element that can be specified in the recipientrequirements is referred to as a “limiting element”. From among userswho satisfy the recipient requirements, the advertisement deliveryserver 1 determines such many users as are expected to raise the numberof clicks during the specified period to at least the desired number ofclicks to be recipients of the advertisement, and makes deliveries ofthe advertisement. Deliveries of an advertisement that are made for thefirst time are referred to as the first deliveries. The number ofrecipient users is referred to as the number of deliveries. As thenumber of deliveries increases, the number of clicks can be expected toincrease. However, the number of clicks to be made during the periodneed not be excessively large as compared to the desired number ofclicks. The reason is that the number of clicks that is at least equalto the desired number of clicks can satisfy the advertiser's desire. Ifan excessively large number of deliveries cause an excessively largenumber of clicks compared to the desired number of clicks, the number ofdeliveries relative to the desired number of clicks becomes large. Thismeans that efficiency in deliveries of the advertisement is reduced andthat the processing load of the advertisement delivery server 1 isunnecessarily increased. Thus, the advertisement delivery server 1determines the number of deliveries, for example, so that the number ofclicks is as close as possible to the desired number of clicks.

There may be a case where after the first deliveries, the actual numberof clicks at a time before the end of the period is not as many as anexpected number of clicks. In this case, the number of clicks at the endof the period is likely to fall short of the desired number of clicks.In such a case, the advertisement delivery server 1 performs additionaldeliveries of the advertisement. At this time, the advertisementdelivery server 1 determines additional recipients so that the expectednumber of clicks at the end of the period is greater than or equal tothe desired number of clicks, so that the expected number of clicks isas close as possible to the desired number of clicks, and so thatefficiency in deliveries of the advertisement increases. How todetermine the additional recipients will be described later.

1-2. Database Structures of Online Marketplace Server

The following describes database structures that the online marketplaceserver 2 has, with reference to FIGS. 3A to 3C. FIG. 3A is a diagramshowing example contents stored in the member information DB 21. Themember information DB 21 stores member information about users who havesigned up for the online marketplace. Specifically, the memberinformation DB 21 stores, for each user, the user's user ID, password,nickname, name, member rank, birth date, age group, gender, zip code,address, area of residence, telephone number, email address, and otheruser attributes in association with each other. The user ID isidentification information of the user. The member rank is a rank thatis assigned to the user based on his or her online marketplace usagepattern. A user assigned a higher rank can receive preferentialtreatment in using the online marketplace. The area of residenceindicates the area where the user lives. For example, the area ofresidence may be a prefecture, a district, or a country.

FIG. 3B is a diagram showing example contents stored in the viewinghistory DB 22. The viewing history DB 22 stores viewing histories.Specifically, every time a web page is viewed, for example, a user ID, aviewed date and time, and a URL are stored in association with eachother in the viewing history DB 22. The user ID indicates the user whoviewed the web page. The viewed date and time indicates the date andtime at which the web page was viewed. The URL indicates the viewed webpage. The advertisement delivery server 1 is capable of identifying astore and an item about which information is displayed on the web page,from the URL of the web page.

FIG. 3C is a diagram showing example contents stored in the purchasehistory DB 23. The purchase history DB 23 stores purchase histories.Specifically, every time an item is purchased, for example, an ordernumber, an order date and time, a user ID, a store ID, an item ID, aproduct code, a category ID, and a unit price are stored in associationwith each other in the purchase history DB 23. The order number is anidentification number that is assigned to an item order. The order dateand time indicates the date and time at which the item was ordered. Theuser ID indicates the user who purchased the item. The store ID isidentification information of the store that sold the purchased item.The item ID is identification information that the store assigned to theitem. The product code is a code number identifying the item. Examplesof the product code include a Japanese article number (JAN) code. Theitem ID and the product code indicate the purchased item. The categoryID is identification information of a category to which the purchaseditem belongs.

1-3. Configuration of Advertisement Delivery Server

The following describes a configuration of the advertisement deliveryserver 1 with reference to FIGS. 2A and 3D to 3F. FIG. 2A is a blockdiagram schematically showing an example configuration of theadvertisement delivery server 1 according to this embodiment. As shownin FIG. 2A, the advertisement delivery server 1 includes a communicationunit 11, a storage unit 12, an input/output interface 13, and a systemcontroller 14. The system controller 14 and the input/output interface13 are connected via a system bus 15.

The communication unit 11 connects to the network NW and controls thestate of communications with the store terminals 3, the user terminals4, and the like.

The storage unit 12 includes, for example, hard disk drives. In thisstorage unit 12, the advertisement DB 121, the advertisement deliveryhistory 122, the click history DB 123, and other databases are created.

FIG. 3D is a diagram showing example contents stored in theadvertisement DB 121. As shown in FIG. 3D, the advertisement DB 121stores, for each advertisement whose deliveries were requested by anadvertiser, an advertisement ID, a store ID, an item ID, a product code,a category ID, advertisement content, delivery requirements, and otherinformation in association with each other. The advertisement ID isidentification information of the advertisement. The store ID indicatesthe store that is the advertiser. The item ID and the product codeindicate an item to be advertised. The advertisement content is contentof the advertisement output to user terminals 4. For example, theadvertisement content may include at least one of characters, an image,a moving image, and a sound. The advertisement content also includes theURL of a web page indicated by a link displayed in the advertisement.

FIG. 3E is a diagram showing example contents included in the deliveryrequirements. As shown in FIG. 3E, the delivery requirements include adesired number of clicks, a specified period, and one or more recipientrequirements. As described above, examples of a limiting element thatcan be specified as a recipient requirement include gender, age groups,areas of residence, member ranks, a web page viewing history, an itempurchase history, a delivered advertisement reception history. Examplesof a limiting element related to the web page viewing history includewhether, how many times, how often, and when a web page was viewed. Aweb page to be viewed may not be specified. Alternatively, a web pagefor a specific item, an item belonging to a specific category, an itemwith a specific attribute, or the like may be specified. Examples of alimiting element related to the item purchase history include whether,how many times, how often, and when an item was purchased. An item to bepurchased may not be specified. Alternatively, a specific item, an itembelonging to a specific category, an item with a specific attribute, orthe like may be specified. Examples of a limiting element related to auser's history of receiving delivery of an advertisement includewhether, how many times, how often, and when the advertisement wasdelivered. An item advertised by the delivered advertisement may not bespecified. Alternatively, a specific item, an item belonging to aspecific category, an item with a specific attribute, or the like may bespecified.

FIG. 3F is a diagram showing example contents stored in theadvertisement delivery history DB 122. The advertisement deliveryhistory DB 122 stores advertisement delivery histories. Specifically,every time deliveries of an advertisement are made, for example, anadvertisement ID, a delivery date and time, the number of deliveries,and a recipient list are stored in association with each other in theadvertisement DB 122. The advertisement ID indicates the deliveredadvertisement. The delivery date and time indicates the date and time atwhich the advertisement was delivered. The number of deliveries is thenumber of recipient users of the advertisement. The recipient list is alist of the recipient users of the advertisement.

FIG. 3G is a diagram showing example contents stored in the clickhistory DB 123. The click history DB 123 stores click histories.Specifically, every time an advertisement is selected, for example, anadvertisement ID, a user ID, and a click date and time are stored inassociation with each other in the click history DB 123. Theadvertisement ID indicates the advertisement in which a link wasselected. The user ID indicates the user who selected the link. Theclick date and time indicates the date and time at which the link wasselected. The URL in a link included in an advertisement delivered bythe advertisement delivery server 1 has been converted into, forexample, a URL of the advertisement delivery server 1. This URLincludes, for example, an advertisement ID and information identifyingthe web page originally identified by the link. When a user selects theadvertisement, the user terminal 4 sends the URL in the link to theadvertisement delivery server 1. In response to this, the advertisementdelivery server 1 registers a click log. The advertisement deliveryserver 1 then returns the URL of the web page originally identified bythe link to the user terminal 4, for example, using an HTTP redirection.The user terminal 4, which has received the URL, accesses the web pageoriginally identified by the link.

The storage unit 12 stores various setting values. The storage unit 12also stores various programs, such as an operating system, a World WideWeb (WWW) server program, a database management system (DBMS), and anadvertisement delivery program. The advertisement delivery program is anexample of an information processing program according to the presentinvention. The advertisement delivery program is a program forperforming various processes related to advertisement deliveries. Thevarious programs may be available from, for example, another serverdevice over the network NW, or may be recorded in a recording medium,such as an optical disk, and be read via a drive device. Theadvertisement delivery program may be a program product.

The input/output interface 13 performs interface processing between thecommunication unit 11 and the storage unit 12, and the system controller14.

The system controller 14 includes, for example, a CPU 14 a, a read onlymemory (ROM) 14 b, and a random access memory (RAM) 14 c. The CPU 14 ais an example of a processor. The present invention can also be appliedto various processors that differ from CPUs. The storage unit 12, theROM 14 b, and the RAM 14 c are each an example of a memory. The presentinvention can also be applied to various memories that differ from harddisks, ROMs, and RAMs.

The advertisement delivery server 1 may include a plurality of serverdevices. For example, a server device that determines recipients of anadvertisement, a server device that makes deliveries of theadvertisement, a server device that manages databases, and other serverdevices may be connected to each other via a LAN or the like.

1-4. Functional Overview of System Controller

The following describes a functional overview of the system controller14 with reference to FIGS. 2B and 4A to 5B. FIG. 23B is a diagramshowing example functional blocks of the system controller 14 of theonline marketplace server 1 according to this embodiment. As shown inFIG. 2B, the advertisement delivery program and other programs, whichare read and executed by the CPU 14 a, enable the system controller 14to function as, for example, a first delivery controller 141, anadditional delivery determiner 142, a further-needed-click-countestimator 143, an adding unit 144, and an additional delivery controller145. The further-needed-click-count estimator 143 is an example ofestimating means of the present invention. The adding unit 144 is anexample of obtaining means, element determination means, and recipientdetermination means of the present invention. The additional deliverycontroller 145 is an example of delivery control means of the presentinvention.

The first delivery controller 141 makes the first deliveries of anadvertisement. The first delivery controller 141 determines recipientsof the advertisement, based on delivery requirements. First, the firstdelivery controller 141 obtains an expected click-through rate (CTR)corresponding to the length of a specified period. A CTR is the ratio ofthe number of users who selected an advertisement to the number of userswho received deliver of the advertisement. Thus, the CTR is calculatedby dividing the number of clicks by the number of deliveries. Anexpected CTR corresponding to the length of a specified period is anexpected CTR until the time when the specified period has elapsed sincedeliveries of an advertisement were made. The expected CTR is an exampleof an expected selection rate. For example, an expected CTR may beprestored for each number of days in the storage unit 12. For example,an administrator of the advertisement delivery server 1 may set theexpected CTR. Alternatively, for example, the system controller 14 maycalculate the expected CTR, based on the advertisement deliveryhistories and the click histories. Alternatively, for example, anexpected CTR may be set for each item category. In this case, the firstdelivery controller 141 may retrieve the expected CTR corresponding to acategory of an item to be advertised.

The first delivery controller 141 divides the desired number of clicksincluded in the delivery requirements by the expected CTR correspondingto the length of the specified period, to calculate the number of firstdeliveries. The first delivery controller 141 also extracts users whosatisfy all recipient requirements from among the users of the onlinemarketplace. From among the extracted users, the first deliverycontroller 141 determines the same number of users as the number offirst deliveries to be first recipients. If the number of users whosatisfy all the recipient requirements is greater than the number offirst deliveries, the first delivery controller 141 may, for example,randomly determine the first recipients from among the users who satisfyall the recipient requirements. The first delivery controller 141 mayincrease the number of first deliveries, which is calculated, forexample, based on the expected CTR and the desired number of clicks, bya predetermined percentage or by a predetermined number.

The following describes a specific example. FIG. 4A is a diagram showingexample delivery requirements. For example, assume that the desirednumber of clicks is 30,000 and that the length of the specified periodis seven days. Also assume that the recipient requirements are that arecipient is a woman in her thirties and that her area of residence isKanto. FIG. 4B shows an example of an expected CTR and the number offirst deliveries. For example, assume that an expected CTR for sevendays is 0.03. In this case, the number of first deliveries is onemillion. For example, when the number of users who are women in theirthirties and whose area of residence is Kanto is two million, the firstdelivery controller 141 makes deliveries of an advertisement to onemillion of the users.

After the first deliveries, the additional delivery determiner 142determines whether to make additional deliveries of the advertisement ata time before the end of the specified period. The additional deliverydeterminer 142 may perform the determination, for example, atpredetermined intervals. The interval between the determinations may be,for example, a predetermined time, a day, a predetermined number ofdays, or a week. In this embodiment, the description assumes that thedetermination is performed at daily intervals.

With each passing day, the additional delivery determiner 142 calculatesan expected number of clicks corresponding to each number of days thathave elapsed since the beginning of the specified period, for example,based on the desired number of clicks included in the deliveryrequirements. An expected number of clicks is an example of an expectednumber of selections of the present invention. The expected number ofclicks is the number of clicks that is expected at a time before the endof the specified period, on the assumption that the number of clicks atthe end of the specified period reaches the desired number of clicks. Tocalculate the expected number of clicks, the additional deliverydeterminer 142 obtains an expected achievement rate for each elapse day.The expected achievement rate is the percentage of the number of clicksexpected until a time before the end of the specified period, on theassumption that the percentage of the number of clicks at the end of thespecified period is 100%. For example, an expected achievement rate maybe prestored for each number of days in the storage unit 12. Forexample, the expected achievement rate may be set or calculated in thesame manner as the expected CTR. The additional delivery determiner 142multiplies the desired number of clicks by the expected achievement ratecorresponding to the number of elapsed days between the beginning of thespecified period and the current time, to calculate the expected numberof clicks.

The additional delivery determiner 142 also obtains the actual number ofclicks made from the beginning of the specified period to the currenttime. An actual number of clicks is an example of an actual number ofselections of the present invention. The actual number of clicks is thenumber of clicks actually made. For example, the additional deliverydeterminer 142 can calculate the actual number of clicks, based on theclick histories. If the actual number of clicks is less than theexpected number of clicks, the additional delivery determiner 142determines that additional deliveries should be made.

If it is determined that additional deliveries should be made, thefurther-needed-click-count estimator 143 estimates how many more clickswill be needed at the end of the specified period. The number of furtherneeded clicks indicates how many clicks less than the desired number ofclicks the number of clicks that are made until the end of the specifiedperiod is. The number of clicks that are estimated to be further neededis referred to as an estimated number of further needed clicks. Forexample, the further-needed-click-count estimator 143 may subtract theactual number of clicks from the expected number of clicks to calculatethe current number of further needed clicks, and may divide this numberof further needed clicks by the expected achievement rate correspondingto the current time to calculate the estimated number of further neededclicks.

The following describes a specific example. FIG. 4C is a diagram showingan example of how to calculate the estimated number of further neededclicks. Assume that the first delivery controller 141 makes deliveriesof an advertisement in accordance with the delivery requirements shownin FIG. 4A and the conditions shown in FIG. 4B. The expected achievementrate at the time when one day has elapsed since the beginning of thespecified period is 0.5. Thus, the corresponding expected number ofclicks is 15,000. Also assume that the corresponding actual number ofclicks is 16,000. In this case, additional deliveries are not made. Theexpected achievement rate at the time when two days have elapsed sincethe beginning of the specified period is 0.75. Thus, the correspondingexpected number of clicks is 22,500. Also assume that the correspondingactual number of clicks is 20,250. In this case, the additional deliverydeterminer 142 determines that additional deliveries should be made. Thefurther-needed-click-count estimator 143 divides the current number offurther needed clicks 2,250 by the corresponding expected achievementrate 0.75, and thus calculates the estimated number of further neededclicks to be 3,000.

The adding unit 144 determines an additional requirement for determiningadditional recipients, from among limiting elements that differ from anyof the recipient requirements. The additional requirement is a limitingelement to be added to the recipient requirements. Specifically, userswho satisfy the additional requirement as well as the recipientrequirements are determined to be the additional recipients. This meansthat the limiting elements are added to the recipient requirements. Todo this, the adding unit 144 obtains an actual CTR of each of thelimiting elements. An actual CTR indicates the ratio of the number ofusers who actually selected an advertisement before a time within thespecified period to the number of users who received deliver of theadvertisement. The actual CTR is an example of an actual selection rateof the present invention. Some of the users who are the first recipientsmay satisfy requirements indicated by the limiting elements that differfrom the recipient requirements. For example, as shown in FIG. 4A, whenthe recipient requirements are that a recipient is a woman in herthirties and that her area of residence is Kanto, some of the users whosatisfy these recipient requirements may have purchased an item, and theother may not have purchased the item. Thus, the adding unit 144obtains, for each limiting element, the ratio of the number of users whoselected the advertisement to the number of users who satisfy arequirement of the limiting element as an actual CTR and who are thefirst recipients. For example, the adding unit 144 can calculate theactual CTRs, based on of the recipient lists of the advertisementdelivery histories and the click histories.

After obtaining the actual CTRs, the adding unit 144 determines anadditional requirement, based on the actual CTRs. For example, fromamong a plurality of limiting elements, the adding unit 144 maydetermine a limiting element that has the highest actual CTR to be anadditional requirement. The reason is that additional deliveries of theadvertisement to users who satisfy a requirement of a limiting elementwith a high actual CTR can be expected to allow a relatively largenumber of clicks to be made with a relatively small number of additionaldeliveries. That is, the advertisement delivery server 1 can efficientlymakes additional deliveries.

After determining an additional requirement, the adding unit 144determines additional recipients, based on the additional requirement,the actual CTR corresponding to the additional requirement, and theestimated number of further needed clicks. For example, the adding unit144 may determine the number of additional deliveries. For example, theadding unit 144 calculates an expected CTR in the remaining days untilthe end of the specified period by users who satisfy all of therecipient requirements and the additional requirement. For example, theadding unit 144 divides the actual CTR corresponding to the additionalrequirement by the expected achievement rate at the current time, tocalculate an expected CTR corresponding to the length of the specifiedperiod. Subsequently, the adding unit 144 obtains an expectedachievement rate corresponding to the remaining number of days betweenthe current time and the end of the specified period. Then, the addingunit 144 multiplies the expected CTR corresponding to the length of thespecified period by the expected achievement rate corresponds to theremaining number of days, to calculate the expected CTR until the end ofthe specified period. The adding unit 144 divides the estimated numberof further needed clicks by the expected CTR to calculate the number ofadditional deliveries. From among users who satisfy all of the recipientrequirements and the additional requirement and who are not the firstrecipients, the adding unit 144 determines the same number of users asthe number of additional deliveries to be the additional recipients.Alternatively, for example, the adding unit 144 may determine a largernumber of users than the number of additional deliveries by apredetermined percentage to be the additional recipients, or maydetermine a larger number of users than the number of additionaldeliveries by a predetermined number to be the additional recipients.

The following shows a specific example. Assume that the first deliverycontroller 141 makes first deliveries in accordance with therequirements shown in FIG. 4A and the conditions shown in FIG. 4B andthat as shown in FIG. 4C, two days later, the additional deliverydeterminer 142 determines that additional deliveries should be made.FIG. 4D shows an example of information about users who have viewed aweb page for an item that has the same attribute as an item to beadvertised and users who have not viewed the web page, among users whosatisfy the recipient requirements. As shown in FIG. 4D, the actual CTRtwo days later of the users who have viewed the specific web page is0.05, and the actual CTR two days later of the users who have not viewedthe specific web page is 0.01. FIG. 4E shows an example of informationabout users who have purchased an item that has the same attribute asthe item to be advertised and users who have not purchased the item,among the users who satisfy the recipient requirements. As shown in FIG.4E, the actual CTR two days later of the users who have purchased thespecific item is 0.03, and the actual CTR two days later of the userswho have not purchased the specific item is 0.02. Thus, the adding unit144 determines a limiting element of having viewed the specific web pageto be an additional requirement. As shown in FIG. 4C, the expectedachievement rate two days later is 0.75, and the expected achievementrate five days later is 0.975. Therefore, the expected CTR of theadditional requirement between two days later and the end of thespecified period is 0.065. The estimated number of further needed clicksis 3,000, and therefore the number of additional deliveries is 46,154.The number of users who satisfy all of the recipient requirements andthe additional requirement and who are not the first recipients is78,000. Therefore, the advertisement delivery server 1 only needs tomake additional deliveries of the advertisement to 46,154 of theseusers. Users who are not first recipients are referred to as unrecipientusers.

When additional deliveries are made to all unrecipient users who satisfyall of the recipient requirements and the additional requirement asadditional recipients, the number of clicks that are expected to be madeby these users in the remaining days until the end of the specifiedperiod is referred to as an expected number of additional clicks. Thisexpected number of additional clicks may far exceed the estimated numberof further needed clicks. For example, as shown in FIG. 4C, the numberof unrecipient users who satisfy the recipient requirements and who haveviewed the specific web page is 78,000. Therefore, the expected numberof additional clicks is 5,070 when the advertisement delivery server 1makes additional deliveries of the advertisement to all these users. Forexample, if the expected number of additional clicks is greater than orequal to the estimated number of further needed clicks by apredetermined percentage or by a predetermined number, the adding unit144 may further determine another additional requirement. The addingunit 144 may then determine additional recipients from among unrecipientusers who satisfy all of the recipient requirements, the firstdetermined additional requirement, and the further determined additionalrequirement. This enables the number of candidates for the additionalrecipients to be closer to the estimated number of further neededclicks. For example, from among limiting elements that differ from anyof the recipient requirements and the limiting elements determined to bethe additional requirements before, the adding unit 144 may determine alimiting element that has the highest actual CTR to be an additionalrequirement. Narrowing additional recipients in accordance with aplurality of additional requirements that have high actual CTRsincreases the probability that the advertisement delivery server 1 moreefficiently makes additional deliveries.

In this case, it is possible that the additional requirements have ahierarchical structure. For example, assume that the first determinedadditional requirement is the top-level additional requirement. Assumethat the level of this additional requirement is 1. Assume that thefurther determined additional requirement is an additional requirementthat is one level lower. Assume that the level of this additionalrequirement is 2. If the third additional requirement is determined, thelevel of this additional requirement is 3. Until the situation that theexpected number of clicks, which is calculated based on the number ofusers who satisfy all of the all levels of additional requirementsdetermined before, is greater than or equal to the estimated number offurther needed clicks by a predetermined percentage or by apredetermined number becomes resolved, the adding unit 144 mayrecursively determine another additional requirement.

The adding unit 144 may determine additional requirements whose level is2 or lower, for example, using the first determined actual CTR.Alternatively, for example, the adding unit 144 may recalculate theactual CTR of each additional requirement, based on the click historiesof users who are the first recipients and who satisfy all levels ofadditional requirements determined before. The adding unit 144 may thendetermine lower levels of additional requirements using the recalculatedactual CTRs.

The adding unit 144 may calculate the expected number of clicks of userswho satisfy all levels of additional requirements determined before, forexample, using the actual CTR of the level-1 additional requirement,using the actual CTR of the bottom-level additional requirement, orusing the actual CTRs recalculated in the above way.

The following shows a specific example. For example, assume that theestimated number of further needed clicks is 3,000 and that a furtheradditional requirement is determined when the expected number ofadditional clicks is greater than 1.05 times the estimated number offurther needed clicks. That is, when the expected number of additionalclicks is greater than or equal to 3,150, a further additionalrequirement is determined. FIG. 5A is a diagram showing example actualCTRs of limiting elements that are candidates for additionalrequirements. As shown in FIG. 5A, for example, there are A-1, A-2, B-1to B-3, C-1, C-2, D-1, and D-2 as candidates for additionalrequirements. Limiting elements whose names begin with the same alphabetare limiting elements with the same element item. For example, thelimiting elements B-1 to B-3 have the same element item. Limitingelements with the same element item are mutually exclusive. For example,the limiting element of woman and the limiting element of man arelimiting elements with the element item of gender. There is no man inwoman, and there is no woman in man. The limiting element that has thehighest actual CTR among the limiting elements shown in FIG. 5A is A-1.Thus, the adding unit 144 determines the limiting element A-1 to be thelevel-1 additional requirement. FIG. 5B is a diagram showing examples ofexpected numbers of additional clicks corresponding to additionalrequirements. The expected number of additional clicks when theadditional requirement is A-1 is 6,000. Thus, the adding unit 144determines a further additional requirement. The limiting element thathas the second highest actual CTR is C-1. Thus, the adding unit 144determines the limiting element C-1 to be the level-2 additionalrequirement. The adding unit 144 counts the number of unrecipient userswho satisfy all the limiting elements A-1 and C-1. The adding unit 144then calculates the expected number of additional clicks, based on thecalculate number of users. The expected number of additional clicks whenthe additional requirements are A-1 and C-1 is 4,000. Thus, the addingunit 144 determines a further additional requirement. The limitingelement that has the third highest actual CTR is C-2. However, thelimiting element C-2 and the limiting element C-1 determined to be theadditional requirement are mutually exclusive. Thus, the adding unit 144rules out the limiting element C-2 as an additional requirement. Thelimiting element that has the fourth highest actual CTR is B-2. Thus,the adding unit 144 determines the limiting element B-2 to be thelevel-3 additional requirement. The expected number of additional clickswhen the additional requirements are A-1, C-1, and B-2 is 3,100.Therefore, the additional requirements are finally settled.

There may be a case where the expected number of additional clickscorresponding to the determined additional requirements is less than theestimated number of further needed clicks. In this case, the adding unit144 may further determine another additional requirement, for example,so that users except users who satisfy the determined additionalrequirements are also determined to be additional recipients. The levelof the additional requirement determined here is the same as that of theadditional requirement previously determined. For example, assume thatthe expected number of additional clicks when the level-1 additionalrequirement is A-1 is 2,500. Thus, the adding unit 144 determines thelimiting element C-1 that has the second highest actual CTR to be afurther level-1 additional requirement. The adding unit 144 extractsuser who satisfy the limiting element C-1, from among unrecipient userswho do not satisfy the limiting element A-1. The adding unit 144 thencalculates the expected number of additional clicks corresponding to thelimiting element C-1, based on the number of the extracted users and theactual CTR of the limiting element C-1. For example, assume that theexpected number of additional clicks corresponding to the limitingelement C-1 is 500. The sum of the expected number of additional clickscorresponding to the limiting element A-1 and the expected number ofadditional clicks corresponding to the limiting element C-1 is 3,000.Therefore, the additional requirements are finally settled. In thiscase, the advertisement delivery server 1 makes deliveries of theadvertisement to users who satisfy at least either the limiting elementA-1 or C-1, among the users who satisfy the recipient requirements.

When determining the same level of additional requirements and thendetermining a lower level of additional requirement, the adding unit 144may determine, for example, users who satisfy one of the additionalrequirements except the last determined one of the upper level ofadditional requirements to be additional recipients. The adding unit 144may then determine the lower level of additional requirement using onlythe last determined additional requirement as an upper level ofadditional requirement. The reason is that the expected number of clicksbased on the number of users who satisfy one of the additionalrequirements except the last determined additional requirement is lessthan the estimated number of further needed clicks. For example, assumethat the adding unit 144 first determines A-1 to be a level-1 additionalrequirement. Also assume that the adding unit 144 further determines B-1to be a level-1 additional requirement because the expected number ofclicks of the additional requirement A-1 is 2,500 and the estimatednumber of further needed clicks is 3,000. Also assume that the expectednumber of clicks of the additional requirement B-1 is 2,000. In thiscase, the adding unit 144 determines users who satisfy the additionalrequirement A-1 to be additional recipients, thus ensuring 2,500expected clicks. The adding unit 144 then determines a lower level ofadditional requirement to further narrow users who satisfy theadditional requirement B-1, accordingly bringing the expected number ofclicks corresponding to the additional requirement B-1, 2,000, close to500, which is the difference between the expected number of clicks ofthe additional requirement A-1, 2,500, and the estimated number offurther needed clicks, 3000.

The additional delivery controller 145 controls deliveries of theadvertisement to the recipients determined by the adding unit 144. Forexample, the additional delivery controller 145 retrieves the emailaddresses of the recipient users from the member information DB 21 andsends each advertisement by email.

1-5. How Information Processing System Works

The following describes how the information processing system S works,with reference to FIGS. 6A to and 9. FIG. 6A is a flowchart showing anexample process in the system controller 14 of the advertisementdelivery server 1 according to this embodiment. FIG. 6A shows a processoverview from the first deliveries of an advertisement to the end of aspecified period. When it is determined based on a stored specifiedperiod that there is an advertisement whose specified period has begun,the system controller 14 retrieves the advertisement ID of theadvertisement from the advertisement DB 121. The system controller 14then performs a first delivery process as shown in FIG. 6A (Step S1). Inthe first delivery process, the system controller 14 makes the firstdeliveries of the advertisement. Subsequently, the system controller 14determines whether a day has elapsed since the first delivery processwas performed (Step S2). If the system controller 14 determines that aday has not elapsed (NO in Step S2), Step S2 is performed again apredetermined time later. On the other hand, if the system controller 14determines that a day has elapsed (YES in Step S2), the process proceedsto Step S3. In Step S3, the system controller 14 determines whether thespecified period has ended. If the system controller 14 determines thatthe specified period has not ended (NO in Step S3), the process proceedsto Step S4. In Step S4, the system controller 14 performs an additionaldelivery control process. In the additional delivery control process,the system controller 14 determines whether to make additionaldeliveries and makes additional deliveries of the advertisement based onthe determination result. Subsequently, the process proceeds to Step S2,and the system controller 14 determines whether a day has elapsed sincethe additional delivery control process was performed. If a day haselapsed, the process proceeds to Step S3. If the system controller 14determines in Step S3 that the specified period has ended, the processshown in FIG. 6A is terminated.

FIG. 6B is a flowchart showing an example of the first delivery processin the system controller 14 of the advertisement delivery server 1according to this embodiment. As shown in FIG. 6B, the first deliverycontroller 141 extracts users who satisfy recipient requirements, fromamong the users of the online marketplace (Step S11). Specifically, thefirst delivery controller 141 extracts the user IDs of users who satisfythe recipient requirements from the member information DB 21, based onthe member ranks, the gender, the age, and the areas of residence storedin the member information DB 21, the viewing history DB 22, the purchasehistory DB 23, the advertisement delivery history DB 122, and otherinformation. Subsequently, the first delivery controller 141 retrievesthe expected CTR corresponding to the length of the specified periodincluded in the delivery requirements from the storage unit 12 (StepS12). Then, the first delivery controller 141 divides a desired numberof clicks included in the delivery requirements by the expected CTR todetermine the number of first deliveries (Step S13). Next, from amongthe extracted users, the first delivery controller 141 determines thesame number of users as the number of first deliveries to be firstrecipients (Step S14). In this step, the first delivery controller 141generates a recipient list that stores the user IDs of the users who arethe first recipients. Subsequently, the first delivery controller 141makes deliveries of the advertisement to the determined first recipients(Step S15). Specifically, the first delivery controller 141 generatesadvertisement emails, based on advertisement content stored in theadvertisement DB 121. The first delivery controller 141 also retrievesthe email addresses corresponding to the user IDs stored in therecipient list from the member information DB 21, and sets the emailaddresses to the address fields of the emails. The first deliverycontroller 141 then sends the generated emails to the recipient users.Subsequently, the first delivery controller 141 registers anadvertisement delivery log (Step S16). Specifically, the first deliverycontroller 141 obtains the current date and time as the delivery dateand time. The first delivery controller 141 then stores the deliverydate and time, a delivery number, the number of first deliveries, andthe recipient list in association with the advertisement ID in theadvertisement delivery history DB 122. After Step S16, the firstdelivery controller 141 terminates the first delivery process.

FIG. 7A is a flowchart showing an example of the additional deliverycontrol process in the system controller 14 of the advertisementdelivery server 1 according to this embodiment. As shown in FIG. 7A, theadditional delivery determiner 142 obtains the actual number of clicksuntil the current time (Step S21). Specifically, the additional deliverydeterminer 142 counts the number of click logs corresponding to theadvertisement ID of the target advertisement, in the click historiesstored in the click history DB 123, as the actual number of clicks. Inthis step, the additional delivery determiner 142 counts a plurality oflink selections by the same user as one selection. Subsequently, theadditional delivery determiner 142 retrieves the expected achievementrate corresponding to the number of days between the beginning of thespecified period and the current time from the storage unit 12 (StepS22). Next, the additional delivery determiner 142 retrieves the numberof first deliveries corresponding to the advertisement ID of the targetadvertisement from the advertisement delivery history DB 122. Then, theadditional delivery determiner 142 multiplies the number of firstdeliveries by the expected achievement rate to calculate an expectednumber of clicks at the current time (Step S23). After that, theadditional delivery determiner 142 determines whether the actual numberof clicks is less than the expected number of clicks (Step S24). If theadditional delivery determiner 142 determines that the actual number ofclicks is not less than the expected number of clicks (NO in Step S24),the additional delivery control process is terminated. On the otherhand, if the additional delivery determiner 142 determines that theactual number of clicks is less than the expected number of clicks (YESin Step S24), the process proceeds to Step S25. In Step S25, thefurther-needed-click-count estimator 143 performs afurther-needed-click-count estimation process.

FIG. 7B is a flowchart showing an example of thefurther-needed-click-count estimation process in the system controller14 of the advertisement delivery server 1 according to this embodiment.As shown in FIG. 7B, the further-needed-click-count estimator 143subtracts the actual number of clicks from the expected number ofclicks, to calculate the current number of further needed clicks at thecurrent time. The further-needed-click-count estimator 143 then dividesthe number of further needed clicks by the expected achievement rate atthe current time, to calculate an estimated number of further neededclicks (Step S41). After Step S41, the further-needed-click-countestimator 143 terminates the further-needed-click-count estimationprocess.

After the further-needed-click-count estimation process, as shown inFIG. 7A, the adding unit 144 sets a target number of additional clicksto the estimated number of further needed clicks (Step S26). Next, theadding unit 144 performs an additional requirement/recipientdetermination process (Step S27).

FIG. 8 is a flowchart showing an example of the additionalrequirement/recipient determination process in the system controller 14of the advertisement delivery server 1 according to this embodiment. Asshown in FIG. 8, the adding unit 144 calculates the current actual CTRfor each limiting element that differs from any of the recipientrequirements (Step S51). Specifically, the adding unit 144 retrieves therecipient list corresponding to the advertisement ID of theadvertisement to be additionally delivered from the advertisementdelivery history DB 122. Based on the recipient list, the adding unit144 extracts, for each limiting element that differs from any of therecipient requirements, a group of users who satisfy the limitingelement, from among the users who are the first recipients and the userswho were determined to be the additional recipients before. For example,the adding unit 144 can extract users who satisfy the limiting element,based on what the member information corresponding to the user ID ofeach recipient user contains, whether there is a viewing history, apurchase history, and an advertisement delivery history corresponding tothe user ID, or what those histories contain. The adding unit 144counts, for each limiting element, the number of users who satisfy thelimiting element. A limiting element that no user satisfies is ruled outas a candidate additional requirement. The adding unit 144 calculates,for each limiting element, the number of users who selected the targetadvertisement, by searching the click history DB 123 for the user IDs ofusers who satisfy the limiting element and the click historycorresponding to the advertisement ID of the advertisement. The addingunit 144 then divides the number of users who selected the advertisementto be additionally delivered by the number of users who satisfy thelimiting element, to calculate the actual CTR.

Subsequently, the adding unit 144 extracts unrecipient users (Step S52).Specifically, the adding unit 144 extracts users who satisfy therecipient requirements from among the users of the online marketplace.The adding unit 144 then extracts users, as unrecipient users, who areneither the first recipients nor the past additional recipients, fromamong the users who satisfy the recipient requirements based on therecipient list retrieved in Step S51.

Subsequently, the adding unit 144 retrieves, from the storage unit 12,the expected achievement rate corresponding to the number of elapseddays between the beginning of the specified period and the current timeand the expected achievement rate corresponding to the remaining numberof days from the current time to the end of the specified period. Theadding unit 144 then divides the expected achievement rate correspondingto the remaining number of days by the expected achievement ratecorresponding to the number of elapsed days until the current time, tocalculate a CTR ratio (Step S53). Next, the adding unit 144 sets anexpected number of additional clicks to 0 and sets a level L to 0 (StepS54). The adding unit 144 also initializes an additional recipient list.After that, from among limiting elements that differ from any of therecipient requirements, the adding unit 144 determines a limitingelement that has the highest actual CTR to be an additional requirement(Step S55). In this step, the adding unit 144 determines the additionalrequirement from among limiting elements that do not have an exclusiverelationship with the recipient requirements. Next, the adding unit 144performs a recursive determination process (Step S56).

FIG. 9 is a flowchart showing an example of the recursive determinationprocess in the system controller 14 of the advertisement delivery server1 according to this embodiment. As shown in FIG. 9, the adding unit 144extracts users who satisfy the additional requirement determined thistime, from among the unrecipient users (Step S61). Subsequently, theadding unit 144 multiplies the actual CTR of the additional requirementdetermined this time by the CTR ratio, to calculate an expected CTR atthe end of the specified period (Step S62). Next, adding unit 144multiplies the number of users extracted in Step S61 by the expected CTRto calculate the number of clicks (Step S63). After that, the addingunit 144 determines whether the sum of the expected number of additionalclicks at the current time and the number of clicks is less than thetarget number of additional clicks (Step S64). If the adding unit 144determines that the sum of the expected number of additional clicks andthe number of clicks is less than the target number of additional clicks(YES in Step S64), the process proceeds to Step S65. On the other hand,if the adding unit 144 determines that the sum of the expected number ofadditional clicks and the number of clicks is not less than the targetnumber of additional clicks (NO in Step S64), the process proceeds toStep S71.

In Step S65, the adding unit 144 adds the user IDs of the usersextracted in Step S61 to the additional recipient list. Subsequently,the adding unit 144 adds the number of clicks to the expected number ofadditional clicks at the current time to update the expected number ofadditional clicks (Step S66). Next, the adding unit 144 determineswhether the level L is 0 (Step S67). If the adding unit 144 determinesthat the level L is 0 (YES in Step S67), the process proceeds to StepS69. In Step S69, from among limiting elements that differ from any ofthe recipient requirements and that have not yet been determined to bethe additional requirements, the adding unit 144 determines a limitingelement that has the highest actual CTR to be an additional requirement.In this step, the adding unit 144 determines the additional requirementfrom among limiting elements that do not have an exclusive relationshipwith the recipient requirements. The adding unit 144 may also determine,for example, a limiting element that has an exclusive relationship withthe additional requirements determined before to be an additionalrequirement. On the other hand, if the adding unit 144 determines thatthe level L is not 0 (NO in Step S67), the process proceeds to Step S68.In Step S68, the adding unit 144 updates the current actual CTR for eachlimiting element that differs from any of the recipient requirements andupper level requirements 1 to L. Specifically, based on the recipientlist, the adding unit 144 extracts users who satisfy all the upper levelrequirements 1 to L, from among the users who are the first recipientsand the users who were determined to be the additional recipientsbefore, as a population. Subsequently, the adding unit 144 extracts, foreach limiting element that differs from any of the recipientrequirements and the upper level requirements 1 to L, users who satisfythe limiting element from the population. After that, the adding unit144 calculates, for each limiting element, the number of users whoselected the advertisement to be additionally delivered, by searchingthe click history DB 123 for the user IDs of users who satisfy thelimiting element and the click history corresponding to theadvertisement ID of the advertisement. The adding unit 144 then dividesthe number of users who selected the advertisement by the number ofusers who satisfy the limiting element to calculate the actual number ofclicks. Next, the adding unit 144 causes the process to proceed to StepS69. The adding unit 144 performs Steps S62, S69, S74, and S75 using thelatest actual CTR. After S69, the adding unit 144 extracts users who donot satisfy the additional requirement determined this time, from amongthe unrecipient users, as new unrecipient users (Step S70). Next, theadding unit 144 causes the process to proceed to Step S61.

In Step S71, the adding unit 144 multiplies the target number ofadditional clicks by a setting ratio stored in the storage unit 12 tocalculate an upper click count limit. The adding unit 144 thendetermines whether the sum of the expected number of additional clicksand the number of clicks is less than the upper click count limit. Ifthe adding unit 144 determines that the sum of the expected number ofadditional clicks and the number of clicks is not less than the upperclick count limit (NO in Step S71), the process proceeds to Step S72. InStep S72, the adding unit 144 adds 1 to the level L. Subsequently, theadding unit 144 determines the additional requirement determined thistime to be an upper level requirement L (Step S73). Next, the addingunit 144 updates the current actual CTR for each limiting element thatdiffers from any of the recipient requirements and the upper levelrequirements 1 to L (Step S74). After that, from among limiting elementsthat differ from any of the recipient requirements and that have not yetbeen determined to be the additional requirements, the adding unit 144determines a limiting element that has the highest actual CTR to be anadditional requirement (Step S75). In this step, the adding unit 144determines the additional requirement from among limiting elements thatdo not have an exclusive relationship with any of the recipientrequirements and the upper level requirements 1 to L. Subsequently, theadding unit 144 determines the users extracted in Step S61 to be newunrecipient users (Step S76). Next, the adding unit 144 recursivelyperforms the recursive determination process (Step S77).

In Step S71, if the adding unit 144 determines that the sum of theexpected number of additional clicks and the number of clicks is lessthan the upper click count limit (YES in Step S71), the process proceedsto Step S78. In Step S78, the adding unit 144 adds the user IDs of theusers extracted in Step S61 to the additional recipient list. After StepS77 or S78, the adding unit 144 causes the process to return back to thecaller of this process, the additional requirement/recipientdetermination process or the recursive determination process.

After the recursive determination process in FIG. 8, as shown in FIG.7A, the additional delivery controller 145 makes deliveries of theadvertisement to the additional recipients, based on the additionalrecipient list (Step S28). This step is the same as Step S15 shown inFIG. 6B. Subsequently, the additional delivery controller 145 registersan advertisement delivery log (Step S29). Specifically, the additionaldelivery controller 145 obtains the current date and time as thedelivery date and time. The additional delivery controller 145 alsocounts the user IDs stored in the additional recipient list to calculatethe number of additional deliveries. The first delivery controller 145then stores the delivery date and time, the number of additionaldeliveries, and the additional recipient list in association with theadvertisement ID in the advertisement delivery history DB 122. AfterStep S29, the additional delivery controller 145 terminates theadditional delivery control process.

As described above, according to this embodiment, the system controller14 makes deliveries of an advertisement to recipients that aredetermined based on recipient requirements, a desired number of clicks,and an expected CTR of the advertisement. The system controller 14 alsoestimates the number of further needed clicks at the end of a specifiedperiod, based on an expected number of clicks and the actual number ofclicks until a time before the end of the specified period. The systemcontroller 14 also obtains, for each of a plurality of limiting elementsthat differ from any of the recipient requirements, the actual CTR of anadvertisement by a group, among recipients of the advertisement, limitedby the limiting element. The system controller 14 also determinesadditional requirements, based on the actual CTRs. The system controller14 also determines additional recipients, based on the additionalrequirements, the actual CTRs of the additional requirements, and theestimated number of further needed clicks. The system controller 14 thencontrols deliveries of the advertisement to the additional recipients.Consequently, this allows for more efficient deliveries of anadvertisement while increasing the probability that the number of clicksof the advertisement will be greater than or equal to a desired numberof clicks.

2. Second Embodiment

The following describes a second embodiment. In this embodiment, whendetermining additional requirements, the advertisement delivery server 1determines the number of additional requirements to determine, dependingon an estimated number of further needed clicks. The larger the numberof additional requirements, the smaller the number of users who satisfyall the additional requirements. Therefore, the larger the number ofadditional requirements, the smaller an expected number of clicks at theend of a specified period. For this reason, the smaller the estimatednumber of further needed clicks, the more additional requirements theadding unit 144 determines. This makes the number of clicks likely to becloser to the estimated number of further needed clicks. For example,the storage unit 12 may store an additional number table. The additionalnumber table is a table that stores estimated numbers of clicks furtherneeded and the corresponding numbers of additional requirements.

The following describes points of difference between processes in thesecond and those in the first embodiment, with reference to FIGS. 8 and9. In the additional requirement/recipient determination process shownin FIG. 8, after Step S54, the adding unit 144 retrieves the number ofadditional requirements N corresponding to the estimated number offurther needed clicks from the additional number table. In Step S55,from among limiting elements that differ from any of the recipientrequirements, the adding unit 144 determines N limiting elements thathave the highest actual CTR to be additional requirements (Step S55).The adding unit 144 then performs the recursive determination process(Step S56). In the recursive determination process shown in FIG. 9, theadding unit 144 extracts users who satisfy all the N additionalrequirements determined this time, from among the unrecipient users. InStep S75, the adding unit 144 determines N additional requirements. InStep S69, the adding unit 144 may determine N additional requirements ordetermine only one additional requirement.

As described above, according to this embodiment, the system controller14 determines the number of additional requirements, depending on anestimated number of further needed clicks. Consequently, additionalrecipients can be efficiently limited.

3. Third Embodiment

The following describes a third embodiment with reference to FIG. 10. Inthis embodiment, the advertisement delivery server 1 adjusts the numberof additional deliveries, depending on the remaining number of daysuntil the end of a specified period. In some cases, the actual number ofclicks is less than expected even after the advertisement deliveryserver 1 made additional deliveries at a time before the end of thespecified period. In this case, the advertisement delivery server 1 canmake additional deliveries again within the specified period. However,when the number of days until the end of the specified period isrelatively small, there is little chance of making additional deliveriesor there is no chance of making additional deliveries again. Thus, ifthe remaining number of days, it is desirable that additional deliveriescause the actual CTR to reliably reach a desired number of clicks at theend of the specified period. For this reason, the smaller the remainingnumber of days until the end of the specified period, the larger theadding unit 144 makes the number of additional deliveries. Except forpoints described below, the third embodiment is basically the same asthe first and second embodiments.

For example, the adding unit 144 may directly adjust the number ofadditional deliveries. For example, the storage unit 12 may store adelivery ratio table. The delivery ratio table is a table that storesthe remaining numbers of days until the end of the specified period andthe corresponding delivery ratios. Each delivery ratio is the ratio ofthe number of additional deliveries after adjustment to the number ofadditional deliveries before the adjustment. The delivery ratio may beset to, for example, 1 or higher. For example, the adding unit 144determines additional requirements and then calculates the number ofadditional deliveries, based on the actual CTRs of the additionalrequirements. The adding unit 144 then multiplies the number ofadditional deliveries by the delivery ratio corresponding to theremaining number of days to determine the number of additionaldeliveries after adjustment. From among unrecipient users who satisfythe additional requirements, the adding unit 144 determines the samenumber of users as the number of additional deliveries to be additionalrecipients.

Also for example, the adding unit 144 may adjust the estimated number offurther needed clicks to indirectly adjust the number of additionaldeliveries. For example, the adding unit 144 may multiply the estimatednumber of further needed clicks by the delivery ratio corresponding tothe remaining number of days, to calculate a target number of additionalclicks. The adding unit 144 may then determine additional requirementsand additional recipients, based on the target number of additionalclicks.

FIG. 10 is a flowchart showing an example of the additional deliverycontrol process in the system controller 14 of the advertisementdelivery server 1 according to this embodiment. In FIG. 10, the samesteps as in FIG. 7A are denoted by the same reference signs. As shown inFIG. 10, after Steps S21 to S25, the adding unit 144 retrieves, from thedelivery ratio table, the delivery ratio corresponding to the remainingnumber of days until the end of the specified period (Step S81).Subsequently, the adding unit 144 multiplies the estimated number offurther needed clicks by the delivery ratio to calculate a target numberof additional clicks (Step S82). Next, the system controller 14 performsSteps S26 to S29.

As described above, according to this embodiment, the system controller14 adjusts the number of additional deliveries, depending on theremaining number of days until the end of a specified period.Consequently, this can increase the probability that the number ofclicks to be added will be greater than or equal to the number offurther needed clicks.

4. Fourth Embodiment

The following describes a fourth embodiment with reference to FIG. 11.In this embodiment, when deliveries of another advertisement have beenmade around the same time as those of a target advertisement, theadvertisement delivery server 1 corrects an estimated number of furtherneeded clicks depending on the deliveries of the other advertisement. Auser who receives another advertisement around the same time as anadvertisement to be additionally delivered may select the otheradvertisement but may not select the advertisement to be additionallydelivered. For this reason, when deliveries of another advertisement aremade around the same time frame, the advertisement delivery server 1increases the estimated number of further needed clicks. Except forpoints described below, the fourth embodiment is basically the same asthe first to third embodiments.

Deliveries around the same time may mean, for example, that the times ofthe deliveries are exactly the same, that the times of the deliveriesare at least partially the same, or that deliveries of anotheradvertisement are made during a period to which the time of deliveriesof an advertisement to be additionally delivered belongs.

For example, the larger the number of deliveries of anotheradvertisement delivered around the same time, the more thefurther-needed-click-count estimator 143 may increase the estimatednumber of further needed clicks. That is because the larger the numberof deliveries of the other advertisement, the more likely the number ofselections of the advertisement to be additionally delivered is to bereduced. For example, the storage unit 12 may store a correction ratiotable. The correction ratio table is a table that stores the numbers ofdeliveries of another advertisement and the corresponding correctionratios. Each correction ratio is the ratio of an estimated number offurther needed clicks after adjustment to an estimated number of furtherneeded clicks before the adjustment. The correction ratio may be set to,for example, 1 or higher.

The further-needed-click-count estimator 143 may correct the estimatednumber of further needed clicks only when an attribute of an itemadvertised by the other advertisement delivered around the same time isthe same as that of an item advertised by the advertisement to beadditionally delivered. This is because a user who has receivedadvertisements for different items that have the same attribute aroundthe same time is highly likely to select only one of the advertisements.Examples of the attribute include categories, functions, specifications,a price range, and a store that sells the item.

FIG. 11 is a flowchart showing an example of thefurther-needed-click-count estimation process in the system controller14 of the advertisement delivery server 1 according to this embodiment.In FIG. 11, the same steps as in FIG. 7B are denoted by the samereference signs. As shown in FIG. 11, after calculating an estimatednumber of further needed clicks (Step S41), thefurther-needed-click-count estimator 143 searches the advertisementdelivery history DB 122 for the advertisement delivery histories ofother advertisements that were delivered around the same time as theadvertisement to be additionally delivered (Step S91). In this step, thefurther-needed-click-count estimator 143 searches for advertisementdelivery histories that have a delivery time around the same time, basedon the delivery date and time included in the advertisement deliveryhistory of the advertisement to be additionally delivered. Subsequently,the further-needed-click-count estimator 143 determines whether theadvertisement delivery histories of other advertisements have been found(Step S92). If the further-needed-click-count estimator 143 determinesthat no advertisement delivery history has been found (NO in Step S92),the further-needed-click-count estimation process is terminated. On theother hand, if the further-needed-click-count estimator 143 determinesthat advertisement delivery histories have been found (YES in Step S92),the process proceeds to Step S93.

In Step S93, based on the found advertisement delivery histories, thefurther-needed-click-count estimator 143 retrieves an attribute of anitem advertised by each of the other advertisements. For example, thefurther-needed-click-count estimator 143 may retrieve a category IDcorresponding to the advertisement ID included in each of the foundadvertisement delivery histories from the advertisement DB 121.Subsequently, the further-needed-click-count estimator 143 determineswhether there is an advertisement advertising an item that has the sameattribute as an item advertised by the advertisement to be additionallydelivered, among the advertisements delivered around the same time (StepS94). For example, the further-needed-click-count estimator 143 maydetermine whether the category ID of the item advertised by each of theother advertisements is the same as that of the item advertised theadvertisement to be additionally delivered. If thefurther-needed-click-count estimator 143 determines that there is noadvertisement advertising the item that has the same attribute as theitem advertised by the advertisement to be additionally delivered (NO inStep S94), the further-needed-click-count estimation process isterminated. On the other hand, if the further-needed-click-countestimator 143 determines that there is another advertisement advertisingthe item that has the same attribute as the item advertised by theadvertisement to be additionally delivered (YES in Step S94), theprocess proceeds to Step S95.

In Step S95, the further-needed-click-count estimator 143 obtains thenumber of deliveries of the other advertisement advertising the itemthat has the same attribute as the item advertised by the advertisementto be additionally delivered from the corresponding advertisementdelivery history. The further-needed-click-count estimator 143 thenretrieves the correction ratio corresponding to the retrieved number ofdeliveries from the correction ratio table (Step S95). Subsequently, thefurther-needed-click-count estimator 143 multiplies the estimated numberof further needed clicks calculated in Step S41 by the correction ratio,to calculate an estimated number of further needed clicks aftercorrection (Step S96). After Step S96, the further-needed-click-countestimator 143 terminates the further-needed-click-count estimationprocess.

As described above, according to this embodiment, when deliveries ofanother advertisement have been made around the same time as those of anadvertisement to be additionally delivered, the system controller 14corrects an estimated number of further needed clicks depending on thedeliveries of the other advertisement. Consequently, the number offurther needed clicks can be properly estimated.

The system controller 14 may also correct the estimated number offurther needed clicks when an attribute of an object advertised by theother advertisement is the same as that of an object advertised by theadvertisement to be additionally delivered. In this case, the number offurther needed clicks can be more properly estimated.

In the above embodiments, the present invention is applied to an onlinemarketplace in which a plurality of stores sell items. However, thepresent invention may be applied to an e-commerce website in which asingle store sells items. A thing to be advertised may be different fromany item. Examples of the thing to be advertised include a service, anevent, a company, an organization, a group, and an individual.

REFERENCE SIGNS LIST

-   1 advertisement delivery server-   2 online marketplace server-   3 store terminal-   4 user terminal-   11 communication unit-   12 storage unit-   121 advertisement DB-   122 advertisement delivery history DB-   123 click history DB-   13 input/output interface-   14 system controller-   14 a CPU-   14 b ROM-   14 c RAM-   15 system bus-   21 member information DB-   22 viewing history DB-   23 purchase history DB-   NW network-   S information processing system

The invention claimed is:
 1. An information processing device fordetermining users to receive an advertisement, the informationprocessing device comprising: at least one memory configured to storecomputer program code; and at least one processor configured to accesssaid computer program code and operate according to said computerprogram code, said computer program code including: delivery controlcode configured to cause at least one of said processor to control by aserver, delivery by email of an initial quantity of the advertisement toa first plurality of recipients among a plurality of possible recipientsafter a commencement of a counting period, wherein the counting periodextends from a beginning of the counting period to an end of thecounting period, wherein delivery requirements of the advertisementinclude: i) a first limiting element for limiting delivery of theadvertisement, and ii) a specified number of selections of theadvertisement by recipients, the first plurality of recipients beingdetermined based on: i) satisfying the first limiting element, ii) thespecified number of selections, and ii) an expected selection rate ofthe advertisement, estimating code configured to cause at least one ofsaid processor to estimate, after the beginning of the counting periodand before the end of the counting period, an estimated number offurther clicks by the end of the counting period, wherein the estimatednumber of further clicks is based on: i) an expected number ofselections indicating how many recipients among the first plurality ofrecipients were expected to select the advertisement within a first timeinterval, and ii) an actual number of selections indicating how manyrecipients among the first plurality of recipients actually selected theadvertisement within the first time interval; obtaining code configuredto cause at least one of said processor to obtain, for each of aplurality of second limiting elements different from the first limitingelement, an actual selection rate of the advertisement by a historicalgroup of recipients among the plurality of possible recipients, whereinthe historical group of recipients is identified in a history databaseas having selected an advertisement in the past and the historical groupof recipients satisfies a corresponding second limiting element amongthe plurality of second limiting elements, element determination codeconfigured to cause at least one of said processor to determine at leastone specific second limiting element to be added to the deliveryrequirements from among the plurality of second limiting elements, basedon the actual selection rates, and recipient determination codeconfigured to cause at least one of said processor to: A) determine anumber of additional deliveries based on: i) the estimated number offurther clicks and ii) the actual selection rate of the advertisementcorresponding to the at least one specific second limiting element, andB) determine additional recipients among the plurality of possiblerecipients of the advertisement from a member information database,based on: i) satisfying the first limiting element, and ii) satisfyingthe at least one specific second limiting element, wherein a number ofadditional recipients is set to the determined number of additionaldeliveries, wherein the delivery control code is further configured tocause at least one of said processor to control delivery, by the server,by email of the advertisement to the determined additional recipients.2. The information processing device according to claim 1, furthercomprising: number determination code configured to cause at least oneof said processor to determine a number of additional limiting elements,depending on the estimated number of further clicks, wherein the elementdetermination code is further configured to cause at least one of saidprocessor to set a number of the at least one specific second limitingelement to be the determined number of additional limiting elements. 3.The information processing device according to claim 1, furthercomprising: adjusting code configured to cause at least one of saidprocessor to adjust a number of additional deliveries of theadvertisement, depending on a remaining time until the end of thecounting period, wherein the recipient determination code causes atleast one of said processor to set the number of additional recipientsto be an adjusted number of additional deliveries.
 4. The informationprocessing device according to claim 1, wherein when deliveries of asecond advertisement have been made separately around the same time asthose of the advertisement, the estimating code causes at least one ofsaid processor to correct the estimated number of further clicks,depending on the deliveries of the second advertisement.
 5. Theinformation processing device according to claim 4, wherein when anattribute of an object advertised by the second advertisement is thesame as that of an object advertised by the advertisement, theestimating code causes at least one of said processor to correct theestimated number of further clicks.
 6. An information processing methodfor determining users to receive an advertisement, the informationprocessing method performed by a computer, the information processingmethod comprising: controlling delivery, by a server, by email of aninitial quantity of the advertisement to a first plurality of recipientsamong a plurality of possible recipients after a commencement of acounting period, wherein the counting period extends from a beginning ofthe counting period to an end of the counting period, wherein deliveryrequirements of the advertisement include: i) a first limiting elementfor limiting delivery of the advertisement, and ii) a specified numberof selections of the advertisement by recipients, the first plurality ofrecipients being determined based on: i) satisfying the first limitingelement, ii) the specified number of selection, and ii) an expectedselection rate of the advertisement; estimating, after the beginning ofthe counting period and before the end of the counting period, anestimated number of further clicks by the end of the counting period,wherein the estimated number of further clicks is based on: i) anexpected number of selections indicating how many recipients among thefirst plurality of recipients were expected to select the advertisementwithin a first time interval, and ii) an actual number of selectionsindicating how many recipients among the first plurality of recipientsactually selected the advertisement within the first time interval;obtaining, for each of a plurality of second limiting elements differentfrom the first limiting element, an actual selection rate of theadvertisement by a historical group of recipients among the plurality ofpossible recipients, wherein the historical group of recipients isidentified in a history database as having selected an advertisement inthe past and the historical group of recipients satisfies acorresponding second limiting element among the plurality of secondlimiting elements; determining at least one specific second limitingelement to be added to the delivery requirements from among theplurality of second limiting elements, based on the actual selectionrates; determining a number of additional deliveries based on: i) theestimated number of further clicks and ii) the actual selection rate ofthe advertisement corresponding to the at least one specific secondlimiting element; determining additional recipients among the pluralityof possible recipients of the advertisement from a member informationdatabase, based on: i) satisfying the first limiting element, and ii)satisfying the at least one specific second limiting element, wherein anumber of additional recipients is set to the determined number ofadditional deliveries; and controlling delivery, by the server, by emailof the advertisement to the determined additional recipients.
 7. Anon-transitory computer readable medium storing thereon an informationprocessing program for determining users to receive an advertisement,the information processing program causing a computer to: controldelivery, by a server, by email of an initial quantity of theadvertisement to a first plurality of recipients among a plurality ofpossible recipients after a commencement of a counting period, whereinthe counting period extends from a beginning of the counting period toan end of the counting period, wherein delivery requirements of theadvertisement include: i) a first limiting element for limiting deliveryof the advertisement, and ii) a specified number of selections of theadvertisement by recipients, the first plurality of recipients beingdetermined based on: i) satisfying the first limiting element, ii) thespecified number of selections, and ii) an expected selection rate ofthe advertisement; estimate, after the beginning of the counting periodand before the end of the counting period, an estimated number offurther clicks by the end of the counting period, wherein the estimatednumber of further clicks is based on: i) an expected number ofselections indicating how many recipients among the first plurality ofrecipients were expected to select the advertisement within a first timeinterval, and ii) an actual number of selections indicating how manyrecipients among the first plurality of recipients actually selected theadvertisement within the first time interval; obtain, for each of aplurality of second limiting elements different from the first limitingelement, an actual selection rate of the advertisement by a historicalgroup of recipients among the plurality of possible recipients, whereinthe historical group of recipients is identified in a history databaseas having selected an advertisement in the past and the historical groupof recipients satisfies a corresponding second limiting element amongthe plurality of second limiting elements; determined at least onespecific second limiting elements to be added to the deliveryrequirements from among the plurality of second limiting elements, basedon the actual selection rates; determine a number of additionaldeliveries based on: i) the estimated number of further clicks and ii)the actual selection rate of the advertisement corresponding to the atleast one specific second limiting element: determine additionalrecipients among the plurality of possible recipients of theadvertisement from a member information database, based on: i)satisfying the first limiting element, and ii) satisfying the at leastone specific second limiting element, wherein a number of additionalrecipients is set to the determined number of additional deliveries; andcontrol delivery, by the server, by email of the advertisement to thedetermined additional recipients.